Clean Data
Aperivue/medsci-skills
A skill your agent uses when a clinical CSV/Excel dataset needs profiling and cleaning before analysis (missing values, outliers, duplicates, type mismatches).
执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。
Install Outlier Detection And Quality Assessment
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessment --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .claude/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .claude/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .agents/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .agents/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .cursor/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .cursor/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MichaelYang-lyx/AIDABench.git --path skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .gemini/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .gemini/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessmentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .github/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .github/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MichaelYang-lyx/AIDABench outlier-detection-and-quality-assessment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MichaelYang-lyx/AIDABench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection .opencode/skills/outlier-detection-and-quality-assessment && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "outlier-detection-and-quality-assessment" agent skill from https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection into .opencode/skills/outlier-detection-and-quality-assessment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "outlier-detection-and-quality-assessment", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
outlier-detection-and-quality-assessment- GitHub stars
- 111
- Used in
- 1 other repo
- Token cost
- ~1k tokens
- SKILL.md length
- 17 words
- Files
- 1
- Skills in repo
- 39
- Repo updated
- First seen
- Licence
- None found
At a glance
执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。
- Works in 5 steps: 加载数据并配置环境 → 基于 IQR 方法识别异常值 → 生成多维度可视化箱线图 → …
- Tasks that involve Data cleaning
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve Excel spreadsheets
What it does
Outlier Detection And Quality Assessment is an agent skill from MichaelYang-lyx/AIDABench. 执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data cleaning and Excel spreadsheets. It works with Microsoft Excel. The repository describes itself as: Code for paper AIDABench: AI Data Analytics Benchmark.
When your agent uses it
- Tasks that involve Data cleaning
- Tasks that involve Excel spreadsheets
Example prompts
- “/outlier-detection-and-quality-assessment”
Requirements
- Python 3
Workflow steps
5 steps, taken from the step headings in SKILL.md.
- 加载数据并配置环境
- 基于 IQR 方法识别异常值
- 生成多维度可视化箱线图
- 偏度与峰度分析及质量评估
- 异常值处理建议（骨架）
What it can do on your machine
Read from SKILL.md and the folder at commit 6dd4206. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Outlier Detection And Quality Assessment loads about 1k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 17 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 17 words (~1,014 tokens).
- name
- outlier-detection-and-quality-assessment
Files
Just SKILL.md in skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection of MichaelYang-lyx/AIDABench.
Open the folder on GitHubat commit 6dd4206
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in MichaelYang-lyx/AIDABench, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Outlier Detection And Quality Assessment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Outlier Detection And Quality Assessment this skillMichaelYang-lyx/AIDABench | 111 | 1 repos | ~1k | Automated safety check: Pass | None | |
| Clean DataAperivue/medsci-skills | 333 | — | ~2k | Automated safety check: Pass | MIT | |
| Dataset Quality Auditzebbern/claude-code-guide | 4.7k | — | ~996 | Automated safety check: Pass | MIT | |
| Clean Dataexplorium-ai/gtm-skills | 185 | — | ~2k | Automated safety check: Pass | MIT | |
| Visual Skillsnpc-live/clawfirm | 156 | — | ~7.4k | Automated safety check: Pass | None | |
| Data Cleaningericrisco/rsc-harness | 180 | — | ~3.6k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Outlier Detection And Quality Assessment
What does Outlier Detection And Quality Assessment do?
执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。. Outlier Detection And Quality Assessment is an agent skill from MichaelYang-lyx/AIDABench.
When should I use Outlier Detection And Quality Assessment?
Outlier Detection And Quality Assessment fits situations like: tasks that involve Data cleaning; tasks that involve Excel spreadsheets.
How do I install Outlier Detection And Quality Assessment in Claude Code?
Run `npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a claude-code`. Or copy the skill folder (skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection in MichaelYang-lyx/AIDABench) into .claude/skills/outlier-detection-and-quality-assessment in your project. Claude Code loads it when a task matches its description.
How do I install Outlier Detection And Quality Assessment in Codex?
Run `npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a codex`. Or copy the skill folder (skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection in MichaelYang-lyx/AIDABench) into .agents/skills/outlier-detection-and-quality-assessment in your project. Codex loads it when a task matches its description.
Can I use Outlier Detection And Quality Assessment in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MichaelYang-lyx/AIDABench --skill outlier-detection-and-quality-assessment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/outlier-detection-and-quality-assessment, .gemini/skills/outlier-detection-and-quality-assessment, .github/skills/outlier-detection-and-quality-assessment and .opencode/skills/outlier-detection-and-quality-assessment in your project.
What does Outlier Detection And Quality Assessment need to run?
SKILL.md names no scripts, command-line tools or credentials: Outlier Detection And Quality Assessment is instructions for the agent only. Our summary lists: Python 3.
Does Outlier Detection And Quality Assessment access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Outlier Detection And Quality Assessment safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Outlier Detection And Quality Assessment use?
No licence was found for Outlier Detection And Quality Assessment or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Outlier Detection And Quality Assessment use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Outlier Detection And Quality Assessment?
Skills that share tags, products or a category with Outlier Detection And Quality Assessment: Clean Data (Aperivue/medsci-skills, 333 stars), Dataset Quality Audit (zebbern/claude-code-guide, 4.7k stars), Clean Data (explorium-ai/gtm-skills, 185 stars) and Visual Skills (npc-live/clawfirm, 156 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Outlier Detection And Quality Assessment?
MichaelYang-lyx (a GitHub user) maintains it in MichaelYang-lyx/AIDABench, which has 111 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on September 28, 2026.
Source: MichaelYang-lyx/AIDABench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.